MODELLING AND MEASURING ATYPICAL EMPLOYMENT

 

 

Under a zero hours contract (ZHC), individuals are not guaranteed work and are paid only for the actual hours of work carried out. Crucially, there is no guarantee of any work being performed, an employer only offers work when and as required; similarly, a worker performs the tasks offered only when and if it suits them. Since early 2013, ZHCs have become one of the highest-profile labour market issues in the UK. Frequent media reports on their use and abuse are polarised between those who see zero hours contracts as the epitome of exploitative, precarious employment, and those who consider them a sign of the efficient functioning of a modern labour market. Yet, despite their salience in public debate, many questions concerning the operation and impact of zero hours contracts (ZHCs) remain unanswered. This is primarily due to a lack of reliable empirical work in the area, arising from a dearth of accurate time series evidence on ZHCs in nationally representative datasets such as the Labour Force Survey.

In the first part of her research agenda, Abigail Adams addresses this gap in knowledge with the help of a novel matched employee-employer panel, the workforce intelligence system of the adult social care sector in the UK. This dataset includes a more accurate measure of ZHCs than other sources, in addition to a host of other worker and employer characteristics. She will develop an economic model that allows for a limited availability of job offers and preferences for flexibility, and then estimate its key parameters using the aforementioned dataset. In so doing, the research will shed light on why individuals accept ZHC work – an absence of preferred alternatives or a preference for the flexibility that such an arrangement affords? - and explore how this varies across different groups of workers. Such results are needed to inform the debate on the regulation of these contracts, which has thus far suffered from a lack of reliable evidence.

A difficulty in measuring ZHCs and other forms of atypical employment accurately is that individuals often lack a sufficient understanding of their contractual situation (International Labour Organisation, 2003; Office for National Statistics, 2014). There are also wider challenges arising from a lack of congruence between employment law taxonomies and the classification of workers in labour market surveys. Lawyers are rarely interested in the label used to describe a particular working arrangement. Under UK employment law, individuals are typically assigned to one of three legal categories, with corresponding levels of employment protection: employee (highest level, incl. unfair dismissal), worker (basic rights, such as minimum wage), self-employed (very little). Atypical working arrangements such as ZHCs would be better identified and understood if researchers focused on operationalising these legal categories.

Dr Adams intends to address this problem in the second part of her research agenda. Together with colleagues in the Oxford Faculty of Law, she will analyse the factors considered in written judgments and claimant forms from employment tribunal cases, and transcripts from interviews with judges. The aim of the project is to identify a set of measurable factors that are good indicators of the legal status of workers. Given this, she will develop a set of questions that can be included in labour market surveys to generate more reliable information on atypical work and the scope of employment protection rights, and then bring together producers and users of labour market statistics to establish how to incorporate these indicators into labour market surveys. In so doing, this work will help to develop a more robust evidence base for future research into atypical work and employment protection legislation, as well as clarifying the key features of work arrangements that determine an individual's legal status. These results will be of crucial importance in informing employment legislation and dispute resolution.

 

 

This project was funded by the Economic and Social Research Council

ES/N017099/1